Develop a six minutes powerpoint presentation that you will present on the topic below (Modelbase design using structured models). You are given a sample extract on the topic to help you write your presentation. You are also free to use your understanding of the topic to develop the presentation.

NB TO EXPAT: Please also provide a story board for the presentation.

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EXTRACT:

A STRUCTURED MODELLING BASED METHODOLOGY TO DESIGN DECISION SUPPORT SYSTEMS

Modelbase design using structured models

A mathematical model consists of elements such as variables, functions, and constraints. A mathematical model is often represented using subscripts, also referred to as indices. Each index has an associated index set. We use capital letters to indicate variables, and small letters to indicate indices.

The following procedure transforms a structured model into a mathematical model.

Given: A structured model consisting of entities, attributes, relationships, functions, and constraints.

Produce: A mathematical model consisting of variables, indices, index sets, functions, and constraints.

Method:

1. Assign an index for each entity in the structured model. The index set for each index is the set of instances of the entity.
2. Assign a variable for each attribute and function in the structured model.
3. The index for a variable is the index assigned for the entity, if the attribute corresponding to the variable is an attribute of an entity the indices assigned for all the entities that are part of the relationship, if the attribute corresponding to the variable is an attribute of a relationship.
4. Transform each function in the structured model into a mathematical representation by substituting the corresponding variables (along with their indices) for attributes and functions mentioned in the right hand side of the function.
5. Transform each constraint using a procedure similar to step 4.
6. The collection of variables, their index sets, functions, and constraints is the mathematical model for the structured model.

The application of the modelbase design procedure to the structured model shown in Fig. 1 results in the following mathematical model.

INDICES

Index Index set

i PLANT

j ITEM

k WAREHOUSE

VARIABLES

Variable Name Attribute/Function Index

C ProdCapacity ij

Q ProdQuantity ij

U UnitProduction_cost j

S UnitShipping__cost ijk

D Demand jk

T Amount_shipped ijk

TPC TotalProduction_Cost

TSC Total_Shipping_Cost

{Note: In addition to the above variables, there will be other variables for plant#, plant_location, Item#, and so on. We have decided to omit these because they do not play any role in the mathematical model itself.}

FUNCTIONS

TPC = F.i~Uj* Qij

TSC = Eijk SukT~jk

TC = TPC + TSC

CONSTRAINTS

Qij < = Cij

EkTijk = Oij

EiTij k = Ojk

Note that the mathematical model is developed for the entire structured model. Depending on the decision maker's objectives, preferences, and risk-taking nature, the entire model or a part of it may be used in the actual DSS design for specific problems.

A key advantage of using the above data and modelbase design procedures is that they separate the model structure, also called a template, from the data. A template model can be used with different sets of data to obtain different results. A template model also facilitates maintenance. Generally, model structure does not change as frequently as data. If data is separated and stored in a database, a DBMS can be used to take care of data maintenance and enforce data integrity. If models and data are integrated tightly, maintenance becomes difficult. However, when the model needs to be solved, it requires the data from the database. We discuss this data/modelbase integration next.